Neural Computing and Applications

, Volume 31, Issue 10, pp 6261–6273 | Cite as

Prediction of permanent deformation in asphalt pavements using a novel symbiotic organisms search–least squares support vector regression

  • Min-Yuan Cheng
  • Doddy PrayogoEmail author
  • Yu-Wei Wu
Original Article


The prediction of asphalt performance can be very important in terms of increasing service life and performance while saving energy and money. In this study, a new hybrid artificial intelligence (AI) system, SOS–LSSVR, has been proposed to predict the permanent deformation potential of asphalt pavement mixtures. SOS–LSSVR utilizes the symbiotic organisms search (SOS) and the least squares support vector regression (LSSVR), which are seen as a complementary system. The prediction model can be established from all input and output data pairs for LSSVR, while SOS optimizes the system’s tuning parameters. To avoid sampling bias and to partition the dataset into testing and training, a cross-validation technique was chosen. The results can be compared to those of previous studies and other predictive methods. Through the use of four error indicators, SOS–LSSVR accuracy was verified in predicting the permanent deformation behavior of an asphalt mixture. The present study demonstrates that the proposed AI system is a valuable decision-making tool for road designers. Additionally, the success of SOS–LSSVR in building an accurate prediction model suggests that the proposed self-optimized prediction framework has found an underlying pattern in the current database and thus can potentially be implemented in various disciplines.


Asphalt mixtures Artificial intelligence Permanent deformation Least squares support vector regression Symbiotic organisms search 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Department of Civil and Construction EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan, ROC
  2. 2.Department of Civil EngineeringPetra Christian UniversitySurabayaIndonesia

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